{"title":"A Job Satisfaction Scale for Tech Workers: Development and Validation in the Global Context","authors":"Amenawon Imuwahen Ehigbochie, Godspower Osaretin Ekuobase","doi":"10.1155/2024/8873743","DOIUrl":null,"url":null,"abstract":"<p>Humanity now lives and works in two worlds—the physical world and the cyber world. Tech workers are employees, not necessarily information technology (IT) professionals, who work in both worlds and seamlessly harness accessible resources in the worlds to meet organizational goals. This category of employees has unique job experiences and is more complicated to manage than the traditional workforce. Job satisfaction—a measurable outcome of employee wellbeing—remains a crucial indicator of an employee’s job experience. This psychological health of employees is usually measured using a job satisfaction scale. However, existing job satisfaction scales for tech workers lack specificity of measurement or cultural inclusivity. This study is, therefore, aimed at developing and validating a job satisfaction scale for tech workers in the global context. The systematic and scoping literature review methods were adopted for initial factors and item extraction. Two separate online surveys were conducted across the globe to randomly solicit tech workers’ acceptance rating of extracted factors and, after the factor selection, the rating of extracted associated items. The accepted numbers of respondents’ responses were 261 and 223, respectively. The Statistical Package for Social Sciences version 22 was used for data adequacy analysis, factor analysis, and Cronbach’s alpha coefficient test. A seven-factor model with 25 items was realized. Confirmatory factor analysis (CFA) using the Analysis of Moment Structure software has been performed on the seven-factor model. The model was further analyzed for organizational effectiveness. A notable finding was that successful validation is not enough to ship psychometric scales to the market—a sound social effectiveness analysis outcome is required. A practical seven-factor job satisfaction scale for tech workers has been developed and validated for the tech industry.</p>","PeriodicalId":36408,"journal":{"name":"Human Behavior and Emerging Technologies","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/8873743","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Human Behavior and Emerging Technologies","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1155/2024/8873743","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHOLOGY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Humanity now lives and works in two worlds—the physical world and the cyber world. Tech workers are employees, not necessarily information technology (IT) professionals, who work in both worlds and seamlessly harness accessible resources in the worlds to meet organizational goals. This category of employees has unique job experiences and is more complicated to manage than the traditional workforce. Job satisfaction—a measurable outcome of employee wellbeing—remains a crucial indicator of an employee’s job experience. This psychological health of employees is usually measured using a job satisfaction scale. However, existing job satisfaction scales for tech workers lack specificity of measurement or cultural inclusivity. This study is, therefore, aimed at developing and validating a job satisfaction scale for tech workers in the global context. The systematic and scoping literature review methods were adopted for initial factors and item extraction. Two separate online surveys were conducted across the globe to randomly solicit tech workers’ acceptance rating of extracted factors and, after the factor selection, the rating of extracted associated items. The accepted numbers of respondents’ responses were 261 and 223, respectively. The Statistical Package for Social Sciences version 22 was used for data adequacy analysis, factor analysis, and Cronbach’s alpha coefficient test. A seven-factor model with 25 items was realized. Confirmatory factor analysis (CFA) using the Analysis of Moment Structure software has been performed on the seven-factor model. The model was further analyzed for organizational effectiveness. A notable finding was that successful validation is not enough to ship psychometric scales to the market—a sound social effectiveness analysis outcome is required. A practical seven-factor job satisfaction scale for tech workers has been developed and validated for the tech industry.
期刊介绍:
Human Behavior and Emerging Technologies is an interdisciplinary journal dedicated to publishing high-impact research that enhances understanding of the complex interactions between diverse human behavior and emerging digital technologies.